Method, system and device for sleep stage determination using frontal electrodes

ABSTRACT

The described embodiments relate generally to methods, systems and devices for sleep stage determination using frontal electrodes. Certain embodiments relate to a system for sleep stage determination comprising a sensing unit and a processing unit. The sensing unit is positioned over a forehead area of a patient and has first, second and third electrodes for positioning at locations on or adjacent the forehead area for detecting electrical potentials of a human head. The processing unit is coupled to the sensing unit for receiving biological signals corresponding to the detected electrical potentials and processing the biological signals to determine a sleep stage of the patient. The processing of the biological signals is based on a plurality of rules.

TECHNICAL FIELD

The described embodiments relate to a method, system and device forsleep stage determination using frontal electrodes. In particular,embodiments involve positioning of at least three electrodes on humanforehead positions.

BACKGROUND

For medical diagnostic purposes, it can be useful to determine the sleepstages experienced by a person during sleep. Such sleep stagedetermination has traditionally been performed in a laboratory setting,in which the patient is asked to sleep while undergoing the testing.Under such conditions, the patient may to experience abnormal sleeppatterns.

The sleep stage determination in such a laboratory setting is commonlyperformed by affixing a plurality of electrodes on the patient's scalpat various standard positions according to the 10-20 system of electrodeplacement. Some electrodes are positioned to senseelectroencephalographic (EEG) signals, while other electrodes may bepositioned to detect electromyographic (EMG) signals orelectrooculographic (EOG) signals. The EEG, EMG and EOG signals may beprovided to a processing system, including, for example, a neuralnetwork for use in determining the stage of sleep experienced by theperson according to the detected signals.

The described embodiments attempt to address or ameliorate one or moreof the disadvantages or shortcomings associated with existing sleepstage determination methods or systems, or to at least provide a usefulalternative thereto.

SUMMARY

The described embodiments relate generally to methods, systems anddevices for sleep stage determination using frontal electrodes. Certainembodiments relate to a system for sleep stage determination comprisinga sensing unit and a processing unit. The sensing unit is positionedover a forehead area of a patient and has first, second and thirdelectrodes for positioning at locations on or adjacent the forehead areafor detecting electrical potentials of a human head. The processing unitis coupled to the sensing unit for receiving biological signalscorresponding to the detected electrical potentials and processing thebiological signals to determine a sleep stage of the patient. Theprocessing of the biological signals is based on a plurality of rules.

The rules may be stored in a data store associated with the processingunit. The processing unit may store data associated with the biologicalsignals internally or it may communicate with an external device.

The sensing unit may comprise a flexible member having the first, secondand third electrodes located thereon. The first electrode may be locatedon the flexible member for positioning adjacent a nasion area of thehead. The second and third electrodes may be located on the flexiblemember for positioning over opposed lateral forehead portions. One ofthe first, second and third electrodes may act as a reference electrode.Conductors may be formed on the flexible member for electricallycoupling the first, second and third electrodes to an output connectorcoupled to the processing unit.

The sensing unit may comprise a fourth electrode located on the flexiblemember intermediate the second and third electrodes for positioning overa central forehead portion. The second and third electrodes may belocated on the flexible member for positioning higher on the foreheadthan Fp1 and Fp2 electrode positions. The fourth electrode may belocated on the flexible member for positioning above the firstelectrode. The first and fourth electrodes may be located on theflexible member for positioning along a vertical center line of thehead. The fourth electrode may be located on the flexible member forpositioning lower on the forehead than a Fz electrode position and mayact as a reference electrode. The second and third electrodes may belocated on the flexible member for positioning laterally beyondrespective Fp1 and Fp2 electrode positions.

The second, third and fourth electrodes may be positioned along a line.The first, second and third electrodes may be positioned in a triangularconfiguration. The triangular configuration may be an isoscelestriangular configuration. The first, second, third and fourth electrodesmay be positioned in a T-shaped, cross-shaped or Y-shaped configuration.The conductors may comprise a printed flexible material. The second andthird electrodes may have a separation of 70 to 110 mm, 80 to 100 mm, orabout 90 mm. The first and fourth electrodes may have a separation of 35to 55 mm, 40 to 50 mm, or about 44 mm.

The processing unit may comprise a signal conditioning unit forreceiving the detected electrical potentials, conditioning theelectrical potentials to generate the biological signals and providingthe biological signals to a processor within the processing unit. Theplurality of rules may be stored in the data store. The plurality ofrules may represent physiological conditions correlated with particularbiological signals. The output connector may be formed at an end of aconnector limb of the flexible member.

The electrical potentials may correspond to at least one of EEG, EOG andEMG signals. A pre-processing unit may be comprised in the processingunit. The pre-processing unit may comprise a wireless transmitter forwirelessly transmitting the biological signals to a receiver of theprocessing unit. The wireless transmitter may be a low-power,short-range transmitter. The first, second and third electrodes may beremovably attachable to the sensing unit. The flexible member maycomprise a flexible plastic substrate or a woven material.

Other embodiments relate to a method of sleep stage determination,comprising receiving electrical potentials corresponding to biologicalsignals from an electrode assembly positioned over a head of a patient;processing the biological signals to determine EEG signals, EOG signalsand EMG signals; and determining a sleep stage of the patient based onthe EEG signals, the EOG signals and the EMG signals and a plurality ofrules.

The rules may be based on empirically derived correlations of EEG, EOGand EMG signal activity with one or more stages of sleep. The electrodeassembly may comprise first, second and third electrodes positioned atlocations on or adjacent the forehead area, the first electrode beingpositioned adjacent a nasion area of the head and the second and thirdelectrodes being positioned over respective laterally opposed foreheadareas. The second and third electrodes may be positioned above andlaterally beyond respective Fp1 and Fp2 positions.

The method may further comprise, prior to the step of receiving,positioning a sensing unit comprising the frontal electrode assemblyover the forehead area. The sensing unit may be configured to senseelectrical potentials corresponding to the biological signals.

The sleep stage may be determined on an epoch by epoch basis. For anepoch, the step of determining may include evaluating the EEG signals,the EOG signals and the EMG signals received during the epoch accordingto the plurality of rules and assigning a sleep stage categorization tothe epoch. The step of determining may include evaluating the EEGsignals, the EOG signals and the EMG signals received during a pluralityof epochs according to the plurality of rules and assigning a sleepstage categorization to the epoch. The step of determining may be basedon previous undecided epochs and last determined epochs and theplurality of rules.

Other embodiments relate to computer readable storage storing computerprogram instructions, which, when executed by a computer processor,cause the computer process to perform the method of: receivingelectrical potentials corresponding to biological signals from anelectrode assembly positioned over a head of a patient; processing thebiological signals to determine EEG signals, EOG signals and EMGsignals; and determining a stage of sleep of the patient based on theEEG signals, the EOG signals and the EMG signals and a plurality ofrules.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are described in further detail below by way of exampleonly, with reference to the accompanying drawings, in which:

FIG. 1 is a front view of a sensing unit for use in sleep stagedetermination;

FIG. 2 is an illustrative side cross-section of the sensing unit of FIG.1, taken along the line A-A;

FIG. 3A is a representative side view of a human head, showing standardelectrode positions and electrode positions according to describedembodiments;

FIG. 3B is a representative plan view of a human head corresponding toFIG. 3A;

FIG. 4 is a schematic representation of the relative positions ofelectrodes on the sensing unit;

FIG. 5 is a block diagram of a system for sleep stage determination;

FIG. 6 is a more detailed block diagram of portions of a system forsleep stage determination corresponding to FIG. 5;

FIG. 7 is a block diagram of an alternative configuration of a systemfor sleep stage determination;

FIG. 8 is a flow chart of a method of sleep stage evaluation accordingto some embodiments; and

FIG. 9 is a flow chart of a method of sleep stage determinationaccording to some embodiments.

DETAILED DESCRIPTION

Referring to FIGS. 1 to 4, embodiments of a device comprising a sensingunit for use in sensing electrical potentials for sleep stagedetermination are shown and described. In the drawings and description,like reference numerals are used to indicate like features, functionsand/or elements as between the drawings.

In this description, reference to terms implying a directionalorientation, such as lateral, vertical, below, above or downward, areintended to be viewed as if the sensing unit is positioned on a foreheadof a human head, while that head is upright. Accordingly, “vertical” isintended to denote directions from the top of the skull toward the neck,while “lateral” is intended to denote positions or directions to oneside of a vertical midline of the head extending along the frontal lineof symmetry of the face (i.e. perpendicular to vertical). For example,in this context, the eyes are laterally spaced relative to the verticalmidline. Thus, “lateral” as applied to the forehead means extendingacross the forehead between the eyebrows and the hairline and, dependingon the shape of the particular forehead, possibly extending aroundtoward the upper temple area.

Terms used herein that imply direction or orientation, such as thosementioned above, are used for ease of description only and are notintended to be a limitation on the described embodiments when they arenot in use on the forehead.

Referring in particular to FIG. 1, there is shown a sensing unit 110positioned on the forehead of a human head 10. Sensing unit 110 has anelectrode array including four electrodes E1, E2, E3 and E4 formedthereon for overlying exposed skin surfaces of the forehead and nasionareas. Electrodes E1, E2, E3 and E4 are used to detect electricalpotentials corresponding to EEG, EMG and EOG signals during a sleepstudy.

Sensing unit 110 comprises a flexible plate-like member 120 formedroughly in a T-shape when viewed from the front while worn on the head10. A lower portion 125 of flexible member 120 projects downwardly fromthe substantially laterally extending body of flexible member 120. Lowerportion 125 houses electrode E3 so as to be positioned to at leastpartly overlie the nasion area or an area adjacent thereto. Depending onthe forehead structure of the head 10, electrode E3 may be positionedslightly above the nasion area, but generally on a centre line extendingvertically through the forehead intermediate the eyes and eyebrows.

Electrodes E1, E4 and E2 are spaced laterally across sensing unit 110.Electrode E4 acts as a ground electrode relative to the measuredpotentials from electrodes E1, E2 and E3. Electrodes E1 and E2 arepositioned in laterally extending wings 127 and 128 located onrespective right and left sides of the head 10 (as seen from thepatient's perspective). Electrodes E1 and E2 and wings 128 and 127 arepositioned widely (laterally) so that, for most forehead sizes andstructures, the electrodes E1, E2 are respectively positioned on theforehead above and laterally beyond a vertical centerline through eacheye. The greater lateral spacing of electrode E1 and E2 allows thesensing of a greater amount of relevant EEG data.

Ground electrode E4 is positioned generally centrally on sensing unit110 within a central area 126 of flexible member 120.

As shown in FIG. 1, flexible member 120 has a connector limb 132extending from a left side (seen from the patient's perspective) thereofand a connector 130 at an end of connector limb 132. Connector 130 isarranged to electrically couple conductors 122 extending through sensingunit 110 to a processing unit 520 (shown and described in relation toFIG. 5), thereby forming an electrical connection between the processingunit and the electrodes E1, E2, E3 and E4 to which conductors 122 areelectrically coupled.

According to one embodiment, sensing unit 110 is formed mostly offlexible materials for placement on a forehead structure and forgenerally conforming to the shape of the forehead structure. Certainparts of sensing unit 110 (for example, those around the electrodes)have an adhesive substance, such as a foam adhesive layer, on anunderside thereof, for affixing the sensing unit 110 to the foreheadprior to conducting the sleep study. Flexible circuitry, comprisingconductors 122, extends through sensing unit 110 from each of theelectrodes E1, E2, E3 and E4 to connector 130. Thus, sensing unit 110can be used with forehead structures of varying shapes and sizes due toits flexibility and ability to conform and adhere to such varyingforehead structures, as required.

Sensing unit 110 is shown in FIG. 2 in partial cross-section, takenalong line A-A of FIG. 1. Flexible member 120 employs a substrate 210 ofa flexible material such as a medical grade polyester film (or othermaterial having similar properties). Substrate 210 forms the top (orupper or outer) layer facing away from the forehead. Substrate 210 hassufficient rigidity to form the base for flexible circuitry to beprinted (or otherwise formed) thereon and enable subsequent conductiveand insulating layers to be formed thereon, while having sufficientflexibility to enable the entire flexible member 120 to bend togenerally conform to the shape of the forehead to which it is to beaffixed.

The substrate 210 may be about 3 to 8 thousandths of an inch thick, forexample. Adhesive 270 is of a relatively weak strength and is used toaffix at least a part of the flexible member 120 to the skin of theforehead. Adhesive 270 is provided on a layer of medical grade adhesivefoam 260 of approximately 1/32 of an inch thickness. The foam 260 isadhered to an insulation layer 220 on the substrate 210 on one side witha relatively strong adhesive 240 and has adhesive 270 on the oppositeside for removable attachment to the test subject. Insulation layer 220is applied directly to the substrate 210 to insulate electricalconductors and is formed of an appropriate epoxy or resin. Theelectrodes E1 to E4 may comprise a silver or silver chloride layerformed on the substrate 210. The substrate 210 has flexible circuittracings formed thereon for constituting the conductors 122 betweenelectrodes E1 to E4 and output connector 130. Such circuit tracings maycomprise silver and preferably have a dielectric layer (such asinsulation layer 220) formed thereover.

Prior to affixation to the forehead, sensing unit 110 may have backingsheets (not shown) on those parts of sensing unit 110 that have anadhesive substance 270 on their undersides for adhesion to the skin.Each such backing sheet is removed immediately prior to adhesion of therelevant part of sensing unit 110 to the corresponding forehead area orareas. For electrodes E1 to E4, an area of conductive gel (not shown),such as hydrogel, is interposed between the respective electrode and theskin surface (instead of the adhesive foam 260), for facilitatingconductivity of electrical signals between the electrodes E1 to E4 andthe skin.

Sensing unit 110 is a generally flat device, as viewed from the user'sperspective, prior to affixation to the test subject. However, sensingunit 110 does have several layers, as described above. In use of sensingunit 110, and with the backing sheets removed, the adhesive foam 260 andelectrodes E1 to E4 are positioned to lie against the skin. These skincontact surfaces may be conveniently referred to as being formed on theunderside of the sensing unit 110. Printed labeling, includingaffixation instructions, may be provided on the side of sensing unit 110that does not contact the skin.

Electrodes E1 to E4 are formed on substrate 210, either directly or on athin priming or separation layer (not shown) coating the underside ofsubstrate 210. Electrodes E1 to E4 are electrically coupled to outputconnector 130 via conductors 122 in the form of flexible circuittracings formed on substrate 210. As with electrodes E1 to E4,conductors 122 may be directly formed on substrate 210 or may beseparated therefrom by a priming or separation layer. Portions offlexible member 120 that are not to be exposed to the forehead (such asconductors 122) are covered by insulation layer 220.

In the embodiment shown in FIG. 2, electrode E4 comprises a silverchloride layer 230 on its outer face for facilitating conductivity withthe skin via a conductive gel in contact with electrode E4. Theconductive gel is provided as a liquid hydrogel and is impregnated intoa porous foam sponge 250 that contacts the skin when the sensing unit110 is positioned on the patient's forehead. Sponge 250 is adhered tosubstrate 210 by an adhesive layer 225 disposed around the electrodes.In order to allow for compression of the sponge during skin contact, agap may be formed on either side of the sponge 250 between the sponge250 and the foam layer 260.

In an alternative embodiment, a substantially more viscous conductivegel can be used instead of the sponge 250 and liquid hydrogel, in whichcase, the adhesive layer 225 and the compression gap are not required.The above impregnated sponge arrangement and the viscous hydrogelarrangement are both commercially available from Vermed, Inc. of BellowsFalls, Vt., USA.

Adhesive layer 270 and conductive sponge 250 may be covered by theprotective backing sheet or layer (not shown) so that the adhesive andconductive qualities of the adhesive layer 270 and conductive sponge 250are preserved until application of flexible member 120 to the forehead.The total thickness of sensing unit 110, including substrate 210, may bein the range of 0.7 to 1.5 millimeters, approximately.

The embodiment shown in FIG. 2 is not to scale, is for purposes ofillustration only and some variations or modifications may be made,depending on the specific requirements of the sensing unit embodimentand methods of forming it.

While the sensing unit embodiments shown and described herein generallyhave a unitary flexible member including two wings and a projectingportion, alternatively each of the areas or portions of the sensing unithaving electrodes may be formed on a separate, but connected, substrate.

In an alternative embodiment of sensing unit 110, metallic diskelectrodes may be used with a flexible member formed of molded plastic,such as a polyvinylchloride (PVC) plastic. In such an embodiment, theplastic is preferably relatively thin and flexible to accommodate thecontours of the wearer's forehead, while having sufficient structuralintegrity and rigidity to maintain the electrodes in their respectivepositions. Such a molded plastic flexible member may be shaped similarlyto flexible member 120 and may employ a suitable adhesive to secure itin place on the forehead. Alternatively, or in addition, a strap orother mechanical means may be used to secure the sensing unit 110 inplace on the wearer's forehead.

Referring in particular to FIGS. 3A, 3B and 4, the positioning ofelectrodes E1, E2, E3 and E4 is described in further detail. FIGS. 3Aand 3B indicate the likely positions of electrodes E1 to E4 on a humanhead, relative to the standard 10-20 electrode positions. As can be seenfrom FIGS. 3A and 3B, reference electrode E3 is positioned adjacent thenasion area. Electrode E3 is located on flexible member 120 so that, formost forehead structures, it will be positioned immediately above thenasion and in between the eyebrows. Electrode E3 is thus positioned onthe vertical centerline of the head in a position lower than the lineextending laterally through frontal positions Fp1 and Fp2.

Electrode E4 is positioned on the midline (vertical centerline) belowfrontal position Fz but above the lateral frontal line extending throughfrontal positions Fp1 and Fp2. Electrodes E3 and E4 are separated by adistance X, as shown in FIG. 4, where X may be about 35 to 55 mm. In oneembodiment, X may be about 40 to 50 mm. In a further embodiment, X maybe about 44 mm.

As shown in FIG. 4, electrodes E1 to E4 are arranged in a T-shapedconfiguration, with reference electrode E3 at a bottom of the T andelectrodes E1, E2 and E4 forming the top line of the T. In alternativeembodiments, the electrode configuration need not be strictly T-shaped.For example, ground electrode E4 may be shifted up or down so that it isnot strictly in line with electrodes E1 and E2.

Further, electrodes E1, E2 and E3 are arranged in a triangularconfiguration, where the distance between electrodes E1 and E3 is thesame as the distance between electrodes E2 and E3, but is not the sameas the distance between electrodes E1 and E2. Thus, electrodes E1, E2and E3 are arranged in an isosceles triangular configuration. Thisconfiguration allows the electrodes to be arranged in sensing pairsE1-E3 and E2-E3 to sense EEG, EOG and EMG potentials, while sensingelectrode pair E1-E2 is also arranged to sense EEG, and EOG potentials.The E1-E3 and E2-E3 electrode pair orientations may be configured to besubstantially orthogonal to each other.

Electrodes E1 and E2 are each laterally separated from electrode E4 by adistance Y that may be the same as distance X or may be differenttherefrom. The total distance (2Y) between electrodes E1 and E2 is,according to one embodiment, between about 70 and 110 mm. In anotherembodiment, the separation of electrodes E1 and E2 is about 80 to 100mm. In a further embodiment, the separation is about 90 mm.

Electrodes E1 and E2 are located on flexible member 120 so as to bepositioned on the forehead at forehead locations above and laterallybeyond standard frontal positions Fp1 and Fp2, respectively. This widerand higher spacing of electrodes E1 and E2 across the frontal areaallows for a greater range and quality of EEG potentials to be detectedthan if the standard Fp1 and Fp2 positions were used. This greater rangecan be used to compensate for the lack of a reference electrodepositioned at A1 or A2 behind the ear.

The specific configuration of electrodes E1, E2 and E3 allows forsimultaneous sensing of EEG, EOG and EMG potentials using a singleelectrode assembly on a flexible member that is easily applied by apatient to his or her own forehead prior to self-initiation of the sleepstudy. Thus, sensing device 110 is easily applied in a home settingwithout the need for the patient to be studied in an artificialenvironment and without the need for a medical technician to affix theelectrodes to the patient's head 10.

In alternative embodiments of sensing unit 110, one or more ofelectrodes E1 to E4 may comprise a needle electrode specificallyconfigured for EMG potential detection. Alternatively, or in addition,one or more of electrodes E1 to E4 may have a wireless transmitterassociated therewith (instead of a conductor 122) for transmittingwireless signals to a nearby receiver, such as is described in U.S.patent application Ser. No. 11/130,221, entitled “Wireless PhysiologicalMonitoring System”, filed May 17, 2005, the entire contents of which ishereby incorporated by reference.

Although not shown in FIG. 1, embodiments of sensing unit 110 may have astrap attachable to each lateral wing 127, 128 for securing sensing unit110 to head 10. Such a strap may be in addition or alternative toadhesive 270 for securing sensing unit 110 in place. In place of astrap, other means for securing the sensing unit to the head may beemployed.

In a further embodiment, electrodes E1 to E4 are removably attachable toflexible member 120. In this embodiment, electrodes E1 to E4 are formedas metallic disk electrodes that have male snap connector parts on aback surface thereof for engaging a corresponding female snap connectorpart positioned on flexible member 120. In this embodiment, conductors122 are electrically coupled to the female snap connector parts, whichform a mechanical and electrical connection with the electrodes via themale snap connector parts on each electrode.

In this embodiment, the underside of flexible member 120 may not employan adhesive to affix the flexible member 120 to the forehead. Rather, astrap or band may be used to secure the flexible member 120 in theappropriate location. In order to affix the electrodes E1 to E4 to theappropriate locations on the forehead and nasion areas, each electrodemay be provided with a portion of adhesive foam around the outside ofthe conductive contact surface of the electrode. Alternatively, theconductive gel on the contact surface of the electrodes may havesufficient adhesive properties to obviate the use of adhesive foamportions around the electrodes.

The removably attachable electrode embodiment allows the flexible member120 to be reusable while the electrodes can be disposed of after eachuse. In this embodiment, the flexible member 120 may be comprised of amaterial having greater flexibility and/or deformation properties thanthe polyester film or PVC described above. A suitable material maycomprise a cloth or other woven material. Alternatively, the flexiblemember 120 may be comprised of a relatively more rigid material, such asPVC, although this rigidity is not strictly required if each electrodeis held in place on the skin by the portion of adhesive materialsurrounding it.

While sensing unit 110 is described as being intended for use in sleepstage determination, the sensing unit 110 may also be used in connectionwith other apparatus or software to record other results of diagnosticsignificance. One example of such other apparatus is a mask forproviding positive airway pressure (PAP) to the patient, such as isdescribed in U.S. patent application Ser. No. 11/131,284, the entirecontents of which is hereby incorporated by reference. Embodiments mayalso be used within the context of an intensive care unit (ICU), forexample to assist in detection of a seizure, stroke, ischemia,burst-suppression or brain hemorrhage or for use in determining a levelof consciousness, sedation or delirium of a patient.

According to alternative embodiments, additional sensors, which may beelectrodes or other forms of sensors, may be provided for positioning atother locations on the head. For example, an additional electrode may beplaced behind or in front of the ear or ears, for use as an active orreference electrode. Such additional sensors may be coupled (forexample, on a unitary substrate) to flexible member 120 for electricalconnection to the processing unit via connector 130. Alternatively, aseparate connector and/or substrate may be used for electricallycoupling the additional sensor or sensors to the processing unit.

While certain embodiments described herein contemplate the use of fourelectrodes E1 to E4 located on the flexible member 120, for each ofthose four electrodes, more than one electrode may be used in place ofthe single electrode. In still further embodiments, the sensing unit 110may employ more than four electrodes at various positions on theflexible member 120. In a further alternative embodiment, the groundelectrode E4 may be omitted or its position varied.

While the configuration of the electrode array of sensing unit 110 isshown arranged in a T-shaped configuration, alternative configurations,for example where the central ground electrode E4 is positioned higheror lower, may be employed. However, electrode configurations thatnecessitate placement of one of the electrodes over a hair-covered partof the scalp or forehead are less desirable than those that allowplacement of the electrodes over hairless areas of the scalp orforehead. Thus, shapes analogous to a T-shape, such as a cross-shape,Y-shape or other shapes having laterally extending wings and adownwardly projecting portion, may be employed to a similar effect tothe embodiments using a T-shaped electrode configuration on the flexiblemember. In one embodiment, the lateral wings of the flexible member 120may extend further laterally and droop down, in a shape similar to ram'shorns, to cover the temple areas on either side of the head. This allowsadditional electrodes to be placed over the temple areas for increasedEEG sensing capability.

Referring now to FIGS. 5 to 9, embodiments of a system and method foruse in processing measured electrical potentials corresponding tobiological signals for sleep stage determination are shown anddescribed. These embodiments employ the embodiments of sensing unit 110described above.

Referring in particular to FIG. 5, there is shown a system 500 for sleepstage determination including the sensing unit 110 and a processing unit520 in communication with, and coupled to, sensing unit 110. Processingunit 520 accepts electrical potentials from sensing unit 110 as input,transforms the received electrical potentials into suitable biologicalsignal data and performs digital signal processing on the biologicalsignal data. Processing unit 520 may also accept instructions via a userinterface 660 (FIG. 6) or provide feedback related to operation ofsystem 500. Processing unit 520 may further communicate over a network560 with a server system 570 in order to, for example, exchange data orinstructions. An example embodiment of processing unit 520 is shown inmore detail in FIG. 6.

Network 560 may comprise a suitable computer or telephone network, suchas a local area network (LAN). Other networks, such as a wireless localarea network (WLAN), the public Internet, or a public switched telephonenetwork (PSTN), may also form part of network 560.

Server system 570 may be used to provide various facilities bettersuited to a centralized system, such as: storage of patient records;storage of sleep data; management of remote processing units;downloading updated software to procession unit 520; facilities forcommunicating other data, such as user instructions or administrativecommands, to remote devices; and facilities for receiving data, such asuser queries or diagnostic information, from remote devices. In oneembodiment, server system 570 may be comprised of a plurality ofphysical computers, not necessarily co-located.

Referring in particular to FIG. 6, processing unit 520 is shown infurther detail. Processing unit 520 contains elements required forprocessing the electrical potentials captured by sensing unit 110.Electrical potentials are received from sensing unit 110 and undergosignal conditioning using a signal conditioning module 650 to transformthe received electrical potentials into suitable biological signal data.Such signal conditioning may include filtering signals in the receiveddata into various frequency bands, as well as amplification and removalof any DC offset.

Conditioned signals are supplied to a digital signal processor 640 foranalysis under the control of, or in combination with, a microprocessor630. Processed biological signal data is stored in a memory 670 bymicroprocessor 630. Microprocessor 630 retrieves stored data from memory670 as needed, for example to provide output or perform furtherprocessing. Microprocessor 630 also transmits data to user interface660, for example, to generate a display to a user of processing unit520. Additionally, microprocessor 630 may receive operationalinstructions from a user via user interface 660.

Signal conditioning module 650 may comprise electronic circuitry on anapplication-specific integrated circuit (ASIC) designed for specificsignal conditioning purposes, including amplification, removal of any DCoffset, analog to digital signal conversion and filtering signals intovarious frequency bands. Alternatively, commercially available discretecomponents may be used to perform each function. Alternatively, asuitable combination of custom and commercial components may be used toperform the signal conditioning.

Digital signal processor (DSP) 640 may be a suitablecommercially-available DSP, general purpose microprocessor, applicationspecific integrated circuit (ASIC), field programmable gate array(FPGA), or a multiple or combination of any of these devices and is usedto perform various calculations that require vector processing of data,such as Fast Fourier Transform (FFT) operations. In an alternativeembodiment, a single module may perform the signal conditioning and DSPfunctions.

Microprocessor 630 may be a suitable commercially-available DSP, generalpurpose microprocessor, ASIC, FPGA, or a multiple or combination of anyof these devices and is used to perform all computation and controlfunctions not performed by other elements of the system, such asconditional branch evaluation, data input/output and device control.

User interface 660 consists of one or more input or output devices forhuman interaction, such as a keyboard, touchpad, printer or visualdisplay. User interface 660 also comprises the output elements requiredto communicate data and command options to a user, such as forms,tables, buttons and other appropriate elements. User interface 660 maybe adapted to accommodate a variety of uses or patients, for example toprovide auditory or Braille output.

Microprocessor 630 may also communicate bi-directionally with anexternal connection 625. External connection 625 may comprise a wirelesscommunication interface or a wired communication interface forcommunication with a remote device or system over, for example, network560. Alternatively, external connection 625 may employ a standardcommunications interface, such as a Universal Serial Bus (USB), tocommunicate with an auxiliary or peripheral device to enable addedfunctionality. Additionally, external connection 625 may also connectdirectly to another processing unit 520 or server system 570.

Microprocessor 630 reads, writes and otherwise manipulates data inmemory 670. The contents of memory 670 may contain both biologicalsignal data and operational instructions associated with a computerprogram to be used in evaluating the signal data. Memory 670 may becomposed of both volatile and non-volatile memory components, includingsolid state, magnetic or optical storage, such as flash programmablememory and hard disk drives, or a combination thereof. In addition,future memory technologies may be employed as they become available andwhere they provide equivalent or enhanced functionality.

Several computer program modules are stored concurrently in memory 670,including: a pre-scoring module 682 for quickly categorizingeasily-identified sleep stages; a single epoch reasoning module 684 foridentifying sleep stages capable of being recognized within a singleobservation interval; a multiple epoch reasoning module 686 foridentifying sleep stages which require signal observation over amultiplicity of observation intervals; and an undecided epochcategorization module 688 for categorizing previously uncategorizedepochs. Each module may exist both as computer program instructions andas a computational representation of its current processing state.

Each of modules 682, 684, 686 and 688 is contained within memory 670 andmay access and update the data store 680 as required, to update signaldata and contextual information, receive updated signal data andcontextual information, or otherwise read or manipulate relevant data.Contextual information includes sleep stage information as well asinformation regarding changes in the parameters used to determine asleep stage. Contextual information may be combined with signal data tocategorize an epoch as belonging to a particular sleep stage. Forexample, if the current epoch follows sleep stage1, AND the Beta1 powerincreases more than 50%, AND the spindle activity is not high, then thecurrent epoch is scored (categorized) as Wake.

The functions of modules 682, 684, 686 and 688 may be further subdividedor supplemented with additional modules, for example to increaseprocessing capacity. Additional detail regarding the function of modules682, 684, 686 and 688 is provided below, particularly in paragraphsdescribing FIGS. 8 and 9 and in pseudo-code describing softwareoperation.

One or more of the above elements, including signal conditioning module650, digital signal processor 640, microprocessor 630, memory 670 andexternal connection 625, may be combined into a single physical device,for example, a field programmable gate array (FPGA).

In an alternative embodiment, processing unit 520 may be subdivided intocomponent units, for example, a pre-processing unit and a mainprocessing unit, such as is shown in FIG. 7. Such an arrangement wouldallow for one main processing unit to service one or more pre-processingunits, which may be helpful in certain clinical settings.

Referring in particular to FIG. 7, there is shown a system 700,comprising: sensing unit 110; a distributed processing unit 719comprising a pre-processing unit 720, wireless communication interfaces(including transceivers) 730 and 740 and a main processing unit 725;network 560; and server system 570. Distributed processing unit 719 isfunctionally equivalent to processing unit 520, but possesses certainfeatures, such as wireless operation and a many-to-one relationship ofpre-processing units to main processing unit, that may make it moresuitable for particular applications.

In this embodiment, sensing unit 110 is coupled (via connector 130) topre-processing unit 720, which performs a subset of the functions, forexample, signal conditioning and digital signal processing, performed byprocessing unit 520. In this embodiment, sensing unit 110,pre-processing unit 720 and wireless interface 730 effectively form asub-system that can be worn by the patient without needing to bephysically connected to, or co-located with, the main processing unit725.

Pre-processing unit 720 uses wireless communication interface 730, whichmay employ a low-power, short-range antenna and a suitable wirelesscommunication protocol, to communicate with wireless communicationinterface 740. Wireless communication interface 740 is connected to mainprocessing unit 725, which performs the remainder of the functions ofprocessing unit 520 not performed by pre-processing unit 720. One mainprocessing unit 725 may communicate with a plurality of pre-processingunits 720.

Main processing unit 725 may further communicate over network 560 withserver system 570. In another alternative embodiment, bothpre-processing unit 720 and main processing unit 725 may communicatedirectly with each other and/or with server system 570 over network 560.

Wireless communication interfaces 730 and 740 employ standardcommercially-available hardware and operate over portions of theelectromagnetic spectrum using common networking standards, for examplethe IEEE 802.11, Bluetooth or IrDA family of protocols. In analternative embodiment, wireless communication interfaces 730 and 740may be of a custom design to enhance certain characteristics, such aslow power or secure operation, to suit the particular application ofsystem 700. Future networking protocols and interfaces, possiblyoperating in other areas of the electromagnetic spectrum, may besubstituted as they become available, where suitable.

In an alternative embodiment, for example, in a clinical or hospitalenvironment, wireless operation may not be desirable or necessary.Therefore, wired communication interfaces, such as members of the IEEE802.3 or 1394 families, may be used in place of wireless communicationinterfaces 730 and 740.

Collection of electrical potentials corresponding to biological signaldata by sensing unit 110 occurs continuously over a period of a numberof hours. At predetermined intervals, called epochs, an evaluationprocess is invoked to evaluate or categorize collected data. In analternative embodiment, epoch frequency may be varied, for example, toincrease the rate of data collection during periods of high activity.

Referring in particular to FIG. 8, there is shown a flow chartillustrating an evaluation process 800, which is an embodiment of oneiteration of the process invoked for an epoch by processing unit 520 ormain processing unit 725 to categorize collected signal data asbelonging to a particular stage of sleep. Processed data, for example,consisting of EEG power spectrum, delta, spindle, K-complex waves,muscle tone, phasic EMG, rapid eye movements (REMs), slow eye movements(SEMs), eye blinks and other contextual information, is gathered at step805 for pre-scoring evaluation at step 810.

Upon completion of pre-scoring step 810, a test is performed at step 815to check if the sleep stage has been determined, based on thepre-scoring. If the sleep stage is determined, contextual information issaved at step 840 and process 800 ends. If the sleep stage cannot yet bedetermined, the evaluation process continues to single epoch reasoning,at step 820.

Upon completion of step 820, a test is performed at step 825 to check ifthe sleep stage has been determined, based on the single epochreasoning. If the sleep stage is determined, contextual information issaved at step 840 and process 800 ends. If the sleep stage cannot yet bedetermined, the evaluation process continues to multiple epochreasoning, at step 830.

Upon completion of step 830, a test is performed at step 835 to check ifthe sleep stage has been determined, based on the multiple epochreasoning. If the sleep stage is determined, contextual information issaved at step 840 and process 800 ends. If the sleep stage cannot yet bedetermined, the data is saved as an undecided epoch, at step 845, andprocess 800 ends. An undecided epoch is equivalent to an unscored epochor undetermined epoch.

Processed data gathered at step 805 is the collection of data obtainedby sensing unit 110 and further conditioned and categorized by one ormore of signal conditioning module 650, digital signal processor 640 andmicroprocessor 630. Processed data gathered at step 805 is stored inmemory 670 in a format suitable for further evaluation.

Pre-scoring step 810, which is performed by microprocessor 630 executingpre-scoring module 682, evaluates processed data 805 to identifypatterns that are easily categorized, for example, such as certaincharacteristics consistent with a waking stage. Upon evaluation ofvarious pre-scoring rules, such as those described below in pseudo-code,it is determined at step 815 whether the sleep stage can be categorizedby the pre-scoring process. If the pre-scoring step was successful atdetermining the sleep stage, the determined sleep stage is assigned tothe epoch under consideration, contextual information is saved at step840 and the current iteration ends. If no sleep stage has beendetermined, the process continues to single epoch reasoning at step 820.

Pseudo-code describing the decision process of one embodiment ofpre-scoring step 810 is shown below. A glossary of acronyms andabbreviations used in the pseudo-code is provided in Table 3 below.

Pre-Scoring

IF (AftM || AftW)  IF (Noisy || MA > 12 || FEMs >= 6 || (AlpPk &&BSIHi)) Cstage = W  ELSE IF (AlpEEG && (ASI >1.2 || FEMs >= 3 || BSIDecrs < 70%))   OR (BtaEEG && (ASI > 0.6 || FEMs >= 3 || Tht Pwr Low))  IF (FstWv Pwr VH && BSIHst && (FSPLow || AlpPwrHi || BSI    Incrs >20%)) Cstage = W ELSE IF (FEMs >= 6 && BSIHi && ASI >= 0.6 && FSPLow)Cstage = W ELSE IF (MA > 15) Cstage = MT IF (Cstage == MT or Cstage ==W)  IF (AftR_W or AftR_M) Cstage = W  ELSE IF (AftR && Cstage == MT)Cstage = R_T ELSE IF (AftR && Cstage == W) Cstage = R_W ELSE    CONTINUE

Single epoch reasoning step 820, which is performed by microprocessor630 executing single epoch reasoning module 684, evaluates processeddata 805 to identify patterns that are capable of being categorizedusing information obtained only from the epoch that is currently beinganalyzed, for example such as REM sleep or transitions between REM sleepand another sleep stage. Upon evaluation of various single epochreasoning rules such as those described below in pseudo-code, a decisionis made at step 825. If the single epoch reasoning step is successful atdetermining the sleep stage, the determined sleep stage is assigned tothe epoch under consideration, contextual information is saved at step840 and the current iteration ends. If no sleep stage has beendetermined, the process continues to multiple epoch reasoning at step830.

Pseudo-code describing the decision process of one embodiment of singleepoch reasoning step 820 is shown below. A glossary of acronyms andabbreviations used in the pseudo-code is provided in Table 3 below.

Single Epoch Reasoning

IF (!AftW && !REMBgrd && !Wakening && !AftR && !BSIHst && Delta > 20%) IF (AftDS || DelPwr VH) Cstage = SD  ELSE Cstage = S2 ELSE IF (!AftW &&!AftDS && MslTLow && MA < 3 && Spindle not    high && ATI < 0.4)  IF(FstWv Pwr Low && FSPLwst && BSIHst)   IF (BSI Incrs > 20% || AftS2)Cstage = REM  ELSE IF (AlpPwrLow && REMs > 0 && BSIHi && Spindle not found)   IF (AftR && BSI Decrs < 50% && FSP Incrs < 200%) Cstage = REM  ELSE IF (!AftR && (BSILow || FSPHst))     IF (AftS2 || S2Wvs) Cstage =S2     ELSE Cstage = S1   ELSE IF (S2Wvs) Cstage = R_S2   ELSE Cstage =R_S1 ELSE IF (REMBgrd)  IF (!S2Wvs && MA < 6 && AftR) Cstage = REM  ELSEIF (S2Wvs) Cstage = R_S2  ELSE IF (MslTVH || AlpPk) Cstage = R_M  ELSECstage = R_S1 ELSE IF ((AftR ||AftRLike) && MA < 6 && Spindle not high&&    AlpPwrLow && !BSILow)  IF (AlpPk || MslTVH)   IF (AftR) Cstage =R_M   ELSE IF (AftR_M or AftR_W) Cstage = W  ELSE IF (! AlpPk && HBSI >6 && LFSP > 6)   IF (!MslTLow && EEGPwr VH && REMs = 0) Cstage = R_M  ELSE IF (BSIHst || (MslTLow && REMs > 0) || (MslTLow &&      FSPLwst))Cstage = REM   ELSE IF (S2Wvs) Cstage = R_S2   ELSE IF (AftR &&(AlpPwrHi || FstWv Pwr High)) Cstage = R_W   ELSE Cstage = R_S1 ELSE IF(!S2Wvs && MA < 1 && (AftR || AftRLike) && ATILow &&    EEGPwr Low &&FstWv Pwr Low)  IF (BSIHi && BSI Decrs < 50% && (FSPLow || FSP Incrs <200%)) Cstage = R_S1 IF (Cstage == UNSCORED) CONTINUE ELSE STOP

Multiple epoch reasoning step 830, which is performed by microprocessor630 executing multiple epoch reasoning module 686, evaluates processeddata 805 to identify patterns that may require data from multiple epochsto categorize sleep stage, for example sleep stages S1 or S2. Uponevaluation of various multiple epoch reasoning rules such as thosedescribed below in pseudo-code, a decision is made at step 835. If themultiple epoch reasoning step is successful at determining the sleepstage, the determined sleep stage is assigned to the epoch underconsideration, contextual information is saved at step 840 and thecurrent iteration ends. If no sleep stage has been determined, thecurrent epoch is categorized as undecided, data associated with theundecided epoch is saved at step 845 and the current iteration ends.

Pseudo-code describing the decision process of one embodiment ofmultiple epoch reasoning step 830 is shown below. A glossary of acronymsand abbreviations used in the pseudo-code is provided in Table 3 below.

Multiple Epoch Reasoning

IF (AlpPk && !SpnPk && Spindle not found && BSIHst)  IF (! AlpPwrLow &&( AlpPwr or FstWv Pwr Incrs > 20%) ) Cstage = W  ELSE Cstage = S1 ELSEIF ((AftW || AftM) && AlpPwrLow && AlpPwr Decrs > 40% && FEMs < 3)  IF(S2Wvs) Cstage = S2  ELSE Cstage = S1 ELSE IF (!AftW && !MslTLow &&BSIHst || FstWv Pwr VH &&    (EEGPwr || FstWv Pwr VH) && !FSPHst)  IF(AftS1 or AftR && Bta1Pwr Incrs > 50%)   IF (Spindle not high) Cstage =W   ELSE IF (AlpPwr Incrs > 50%)    IF (MslTVH) Cstage = MT    ELSECstage = W   ELSE Cstage = S1  ELSE IF (AftS2 || AftDS && Bta2PwrIncrs > 100% && BSI VH)   IF (FstWv Pwr High && Spindle not high)    IF(MA > 2 || FSPHi) Cstage = MT    ELSE Cstage = W   ELSE IF (Spindle nothigh && S2Wvs) Cstage = S2   ELSE Cstage = S1  ELSE IF (BSI VH &&FSPLwst)   IF (FstWv Pwr High && AftW or AftM) Cstage = W   ELSE IF(EEGPwr VH) Cstage = MT   ELSE IF (AlpPwrLow) Cstage = S1  ELSE IF(BSIHi && REMs >= 4)   IF (Spindle not high && FstWv Pwr High) Cstage =W   ELSE IF (S2Wvs) Cstage = S2   ELSE Cstage = S1 ELSE IF (MA >= 3)  IF((BSIHi && FSPLow) || FstWv Pwr VH || (AftW || AftM)) Cstage = W  ELSEIF (S2Wvs && !BSIHst) Cstage = S2  ELSE IF (FSPHst) Cstage = S2  ELSECstage = S1 ELSE IF (AftS2 || AftDS)  IF (MslTVH && AlpPwr Incrs > 200%&& BSIHi) Cstage = W  ELSIF (AftDS && EEGPwr Incrs > 50% && DeltaIncrs > 10%) Cstage = S3  ELSE IF (!BSIHi && S2Wvs) Cstage = S2  ELSECstage = S1 ELSE IF (AftS1 && FstWv Pwr High && AlpPwr Incrs > 20% &&   FstWv Pwr Incrs > 20% && BSIHi) Cstage = W ELSE Cstage = S1

Referring in particular to FIG. 9, there is shown a flow chartillustrating a process 900 describing operation of one embodiment of asleep stage determination system, such as system 500 or 700. For eachobservational interval or epoch, which may be at a predeterminedfrequency or at a variable frequency influenced by prior epochs, rawdata, sample status and contextual information is collected at step 905.

Collected data for the current sample is evaluated at step 910 todetermine if it can be categorized as abnormal. Unless the sample isabnormal, the process continues to a full evaluation branch, beginningat step 945. The sample may be considered to be abnormal if it containsno signal data or only background noise, for example. This may indicatea fault in the sensing unit 110 or processing unit 520 or may be due toa disconnection of the sensing unit 110 from processing unit 520.

In the event that the current sample is identified as abnormal at step910, a set of branch logic rules is evaluated, to diagnose system stateand identify sleep stage, if possible. The diagnostic process begins atstep 915 by first determining whether the system has been instructed tostop recording data, for example, if a patient or other person hasissued a command through user interface 660. If so, the current sleepstage is marked as undecided at step 920. If the system has not beeninstructed to stop recording, a test is performed by processing unit 520at step 925 to identify whether connecting sensing unit 110 has beendisconnected from processing unit 520. This may occur intentionally, forexample when the patient gets out of bed and leaves the room.

When the sensing unit 110 is disconnected from the processing unit 520,the input conductors of the processing unit 520 may pick up low levelbackground noise. The processing unit 520 is configured to compare thereceived low level background noise to a noise level threshold and/orfiltering circuit to determine whether the received noise is consistentwith a disconnection. Alternatively, the processing unit 520 maycomprise a circuit to sense when the connector 130 is connected ordisconnected from the corresponding connecting part on or associatedwith processing unit 520. If the sensing unit 110 is determined byprocessing unit 520 to be disconnected, the current sleep stage iscategorized as wake at step 930. Otherwise it is marked as unscorable atstep 935

Upon completion of diagnostic tests, a further test is performed toidentify if there exist previous undecided epochs at step 940. If thereare none, the current iteration of process 900 ends. If there existprevious undecided epochs, an evaluation process is invoked at step 995a to determine previous undecided epochs, before process 900 is ended.

If the sample status is normal at step 910, signal preconditioning isperformed at step 945 prior to EEG, EOG and EMG analysis at steps 950,955 and 960, respectively. Step 945 is performed by signal conditioningmodule 650, whereas digital signal processor 640 and microprocessor 630perform steps 950, 955 and 960. After signal analysis at steps 945through 960, staging reasoning is conducted at step 965 using a processsuch as that described above with respect to FIG. 8. Upon completion ofstaging reasoning step 965, a set of rules is evaluated, beginning atstep 970, to either complete the current iteration of process 900 orinvoke an evaluation module to determine previous undecided epochs.

For each of steps 950, 955 and 960, the respective EEG, EOG and EMGsignal analysis is performed in order to determine variouscharacteristics and/or events or parameters indicated by the signals.This analysis may include suitable digital signal processing, including,for example, filtering, sampling Fourier transforms, or thresholdcomparisons. Such analysis may be carried out in the time domain orfrequency domain, as appropriate. For example, the analysis may includeanalysis of the power spectral density in the frequency domain. Steps950, 955 and 960 may be performed in the sequence indicated or the orderof these steps may be changed or they may be performed simultaneously.

In the signal preconditioning step 945, the biological signal data isdigitized and amplified, if necessary, by signal conditioning unit 650.Further, digital signal processor 640 processes the biological signaldata to obtain the EEG, EMG and EOG signal data (as described furtherbelow), after which the EEG, EMG and EOG signal data are analyzed (asdescribed further below) to provide the processed data referred to abovein relation to step 805.

If the current sleep stage is determined at step 970 and there are noprevious undecided epochs found at step 985, microprocessor 630 savescontextual information at step 990, for example, to data store 680, andends the current iteration. If the current sleep stage is determined atstep 970 and there are extant previous undecided epochs at step 985, anevaluation process is invoked to determine previous undecided epochs atstep 995; upon completion of which the current iteration ends.

If the current sleep stage is not determined at step 970, the processwill save the current epoch with previous undecided epochs at step 975,for example, to data store 680. If there exist 6 previous undecidedepochs at step 980 an evaluation process is invoked to determineprevious undecided epochs at step 995; upon completion of which thecurrent iteration ends. If there are fewer than 6 previous undecidedepochs at step 980, the current iteration ends immediately. Using 6 asthe upper limit of previous undecided epochs assumes epochs of 30seconds and that the 3 minute smoothing rule applies, whereby if a Kcomplex or spindle is not seen within 3 minutes of the previous Kcomplex or spindle, the sleep stage defaults to stage one sleep (S1). Apredetermined number other than 6 may be used in step 980 according toalternative configurations, for example where shorter or longer epochsare used.

The evaluation process to determine previous undecided epochs at step995, which is performed by undecided epoch categorization module 688,evaluates prior undecided epochs and last detected epochs, notnecessarily in sequential order, to identify patterns that could nototherwise be identified.

Pseudo-code describing the decision process of one embodiment of adetermination of previous undecided epochs, such as that at steps 995and 995 a, is shown below. A glossary of acronyms and abbreviations usedin the pseudo-code is provided in Table 3 below.

Determine Previous Undecided Epochs

IF (Only one epoch && PUE == R_W, R_S1, R_S2 or R_M)  IF (PUE == R_W)Cstage = W  ELSE IF (PUE == R_S1) Cstage = S1  ELSE IF (PUE == R_S2)Cstage = S2  ELSE IF (PUE == R_M) Cstage = MT ELSE IF (NDE == W)  LOOPthe Previous Undecided Epochs List   IF (PUE == REM_S1) Cstage = S1  ELSE IF (PUE == R_S2) Cstage = S2   ELSE IF (PUE == R_M) Cstage = MT  ELSE Cstage = W ELSE IF (NDE == REM)  LOOP the Previous UndecidedEpochs List   IF (PUE == R_W, R_M, W or MT)    IF (LDE == W or MT)Cstage = W    ELSE Cstage = MT   ELSE Cstage = REM ELSE IF (NDE == MT) LOOP the Previous Undecided Epochs List   IF (PUE == R_S1) Cstage = S1  ELSE IF (PUE == R_S2) Cstage = S2   ELSE Cstage = W ELSE  LOOP thePrevious Undecided Epochs List   IF (LDE == S2) Cstage = S2   ELSE IF(LDE == REM) Cstage = REM   ELSE IF (PUE == R_W or R_M) Cstage = MT  ELSE IF (PUE == R_S1) Cstage = S1   ELSE IF (PUE == R_S2) Cstage = S2  ELSE Cstage = NDE

Upon completion of the determination of previous undecided epochs atsteps 995 and 995 a, contextual information for the relevant epochs issaved in a data store, such as data store 680.

Processing and analysis of the biological signal data to obtain the EEG,EMG and EOG data may be performed as described below. The EEG signalsare derived from channels associated with electrode pairs E1-E3 andE2-E3. The EEG signals are obtained by filtering the biological signaldata with a band pass filter to obtain frequencies between 0.5 and 30Hz.

Each epoch of 30 seconds is divided into 10 equal segments and each3-second data segment is subject to a Fast Fourier Transform (FFT) toobtain the power spectral density for each EEG sub activity. Table 1below shows the frequency bands for a number of recognized EEG subactivities.

TABLE 1 Frequency ranges of EEG sub activities Frequency Alpha Beta1Beta2 Delta Sigma Theta Low 7.5 16.0 20.0 1.0 12.0 3.0 High 9.5 20.028.0 2.5 15.0 7.0

Thus, for example, for each 3 second data segment, digital signalprocessor 640 calculates the power of the EEG signals in the Alpha bandbetween 7.5 and 9.5 Hz, and so on for each of the other EEG subactivities. In addition to the power spectral analysis of each 3-seconddata segment, several parameters are calculated by DSP 640, including aBeta/Sigma index (BSI), an Alpha/Theta index (ATI) and the frontalspindle (FSP). The BSI is the ratio between the power of the Beta2 bandand that of the Sigma band. The ATI is the ratio between the power ofthe Alpha band and that of the Theta band. The FSP is the calculatedspectral power of the sigma band.

Further features are extracted from the EEG signal data that involvedetermination of the total duration for which the signal data is withina certain amplitude range for each epoch. Specifically, Delta, Spindleand K-complex activities are extracted from the EEG signals, based onthe frequency and amplitude parameters listed in Table 2 below.

TABLE 2 Parameters for detection of delta, spindle, K-complex ParametersDelta Spindle K-complex Filter frequency (Hz) 0.5-3.5  9.0-15.0 3.0-7.0Amplitude range (μV)  35-150 15-60 30-70

The parameters listed in Table 2 are used to calculate the proportion ofthe epoch for which the EEG signal data is within the amplitude rangeindicated for the listed delta, spindle and K-complex frequencies. Forexample, if greater than 50% of the epoch has signals in the amplituderange of 35 to 150 μV for delta frequencies between 0.5 and 3.5 Hz, thenthis information may be used to determine that the epoch should bedecided as belonging to deep sleep stage S4. If greater than 20% of theepoch is within the amplitude range for the delta frequencies, then theepoch may be decided as belonging to deep sleep stage S3. Deep sleepstages S3 and S4 may be collectively scored as “deep sleep” if theamplitude range for the delta frequencies exceeds a minimum threshold.Such a minimum threshold is configurable, but may be between 2% and 20%,for example.

The EMG analysis of the biological signal data is performed based on thesignals received from channel E1-E2 and band-pass filtered between 20and 40 Hz. The EMG analysis involves calculation of tonic and phasicactivities of muscles in the forehead and vicinity. Tonic activity isassociated with a relaxed, restful state and is referred to also asmuscle tone or tonus. Tonic activity is used to detect changes in muscletone for REM and NREM sleep. Phasic activity is associated with suddenincreases in muscle activity and is used for the detection of movementarousal.

To avoid EMG bursts that may be associated with the phasic activity,which can be a result of a muscle twitch or movement, obscuring thetonic activity, the tonic activity is calculated using theinter-quartile range method, instead of integrating the rectified EMGdata of the whole epoch. The inter-quartile range is calculated as thedifference between the 75th percentile of sample amplitudes (oftencalled Q3) and the 25th percentile (called Q1). The inter-quartile rangeis also sometimes called the H-spread. Period analysis is used to detectpeaks in the EMG signal data and the amplitudes of the detected peaksare sorted and the muscle tone is then calculated as the differencebetween Q3 and Q1. The calculated EMG tonus is used as a threshold todetect EMG burst phasic activities.

EMG burst detection is performed in a similar manner to the EEG featureextraction described above, but with a frequency range of 10 to 40 Hz.If any EMG bursts are detected in an epoch, the 3-second data segmentsincluding the detected EMG bursts are eliminated from consideration andthe rest of the data segments in the epoch are used to again calculatethe EMG tonus. Additionally, DSP 640 determines the average amplitude ofthe EMG tonus, as this may be relevant to determination of which sleepstage the epoch should be assigned to. For example, if the averageamplitude of the EMG tonus is low, then this indicates a REM sleepstage.

For the EOG analysis, left and right EOG signal data are extracted fromthe biological signal data via channels E1-E3 and E2-E3 band-passfiltered between 0.5 and 30 Hz. The EOG signal data are analyzed by DSP640 for eye activities, including eye blink, rapid eye movement and sloweye movement. The EOG signal data is analyzed with respect to anamplitude threshold, frequency range (peak to peak intervals), risingslope and falling slope of the EOG signal wave form to detect eyemovements. Wave forms in the EOG signal data corresponding to eyemovements are detected separately between the left and right EOGchannels. Only those eye movements that are negatively correlated fromleft and right EOG channels are considered as true.

Some high amplitude (up to several hundred micro volts), low frequency(0.1 to 1.0 Hz) waveforms may be detected in frontal channels. Thewaveforms may be, for example, EEG delta waves, eye movement activities,or signal noise generated by body movements or other sources. Withlimited information available from the frontal channels, it may bedifficult to identify the source of such waveforms, which in turn mayresult in difficulties in determining the sleep stage. For example,false detection of eye movements or delta activities may be caused bynoise associated with body movements. As a result, it may be difficultto distinguish Wake from stage 1, stage 2 from deep sleep, REM fromstage 1, and Wake from deep sleep when alpha intrusion occurs in deepsleep.

In one embodiment, one or more body movement sensors may be used fortransmitting signals to processing unit 520 or pre-processing unit 720over a body movement channel. Information or signals received over thebody movement channel can be helpful for sleep staging with frontalchannels by assisting to identify the source of the high amplitude slowwaveforms (HASWs). For example, when body movement is detected (with thebody movement channel), the HASWs can be considered to be noise and theepoch can be scored as either Wake or MT (movement time). Further, ifthe epoch immediately follows or precedes a Wake stage, or if there isdominant alpha activity found in the current epoch, then the epoch canbe scored as Wake. Otherwise, the epoch is scored as MT.

When no body movement is detected, the HASWs can be regarded as eyemovements or delta activities and the stage of the epoch can thereforebe narrowed down to Wake, REM or S1 if the background activities aredominated by fast activities (alpha, beta activities); or the epoch isscored as S2 or delta sleep if the dominant activities are slowwaveforms (delta activities). The exact stage is determined by otherinformation, for example such as contextual information, EEG powerspectra, and percentage of duration of detected delta activities overthe epoch.

The one or more body movement sensors for providing signal data over thebody movement channel are positioned on, or relative to, a part of thebody away from the head. Such sensors may sense movement by use of oneor more accelerometers affixed to the body or they may sense movement bydetection of EMG signals derived from an EMG sensor, for example.Alternatively, the body movement sensors may be located away from thebody and may employ or promote movement detection techniques, such asare known in the art, including, but not limited to, optical imaging. Anexample of a suitable accelerometer for use in the one or more bodymovement sensors is an accelerometer made by FreeScale Semiconductor,Inc. of Austin, Tex. under the MMA7260Q product series.

The body movement sensors may be coupled to processing unit 520 orpre-processing unit 720 directly or via sensing unit 110. Communicationof the signal data obtained by the body movement sensors to processingunit 520 or pre-processing unit 720 may be by way of a wired or wirelessconnection. If an EMG signal detection component is used in the one ormore body movement sensors, it may be coupled with a wirelesstransmitter, as described in U.S. patent application Ser. No.11/130,221.

Provision of the described means for detecting body movement enables theidentification of HASWs in each epoch being considered, which in turnassists in determining the correct sleep stage of the subject.

While the above description provides examples of embodiments, it will beappreciated that some features and/or functions of the describedembodiments are susceptible to modification and change without departingfrom the spirit and principles of operation of the describedembodiments. Accordingly, what has been described is intended to beillustrative of the invention and the described embodiments, rather thanbeing a limiting and/or exclusive definition.

TABLE 3 Glossary of terms, acronyms and abbreviations Acronym orAbbreviation Description and Definition AftDS The immediate previousepoch is scored as Deep Sleep (S3 or S4) AftM The immediate previousepoch is scored as MT AftR The immediate previous epoch is scored as REMAftRLike The immediate previous epoch is scored as R_M, R_W, R_S1 orR_S2 AftR_M An epoch which is scored as Movement Time for which theimmediate previous epoch is scored as REM AftR_W An epoch which isscored as Wake for which the immediate previous epoch is scored as REMAftS1 The immediate previous epoch is scored as S1 AftS2 The immediateprevious epoch is scored as S2 AftW The immediate previous epoch isscored as Wake Alp EEG alpha sub band: 7.5~9.5 Hz AlpEEG Alpha type EEG:Peak found in the alpha sub band in Wake epochs. AlpPk Peak found in thealpha sub band on EEG power spectra AlpPwr EEG power of spectra of alphasub band AlpPwrLow AlpPwr is low when it is < the average AlpPwr ofprevious S1 epochs AlpPwrHi AlpPwr is high when it is: >2 times of theaverage AlpPwr of previous S1, OR > Average AlpPwr of wake epochswithout eye movements ASI Ratio of Alpha and Spindle band EEG powerspectra ATI Alpha Theta Index: Ratio of Alpha and Theta band EEG powerspectra ATILow Alpha Theta Index Low: when the ratio of alpha and thetasub bands power of spectra is <0.4. Bta1 EEG beta1 sub band: 16~20 HzBta1Pwr EEG power of spectra of Bta1 sub band Bta2 EEG beta2 sub band:20~28 Hz BtaEEG Beta type EEG: Peak found in the beta sub band in Wakeepochs. Bta2Pwr EEG power of spectra of Bta2 sub band BtaPk Peak foundin the Bta1 sub band on EEG power spectra BSI Ratio of Bta2 and Spindleband EEG power spectra BSIHi Current BSI level is high if it is notBSIHst, AND: >50% of its average over previous S1, REM and Wake epochs,OR >2 times its average over previous S2 epochs; >1.5 BSIHst Current BSIlevel is highest if it is: > its average over previous S1, REM epochs or80% of wake epoch average, OR >2.0 AND >50% of its average over previousS1 epochs, OR >3.0 BSILow Current BSI level is low if it is not BSIHst,not BSIHi, not BSILwst, AND: < its average over previous SD epochs, OR<1.2 times its average over previous S2 epochs, OR <0.5 BSILwst CurrentBSI level is lowest if it is not BSIHst, not BSIHi, AND: << Of itsaverage over previous S2 epochs, OR <20% of its average over previousREM epochs, OR <0.1 BSI VH BSI very High if: BSIHst or BSIHi and BSIincreased more than 50%. Cstage Stage of current epoch (being analyzed)Decrs Decreased compared to last epoch (e.g. Alpha Incrs >0.2 = alphadecreased more than 20% than last epoch) Del EEG delta sub band: 1~2.5Hz DelPwr VH EEG power of spectra of delta sub band is very high, whenit is: >5 × 10⁷, μV² AND >2 times its value in previous S2, AND ATI<0.4. Delta Duration of detected delta waves (in seconds). EEGPwr EEGpower of spectra of the sub band ranging from 1~28 Hz. EEGPwr Low EEGPwris low when it is: <10% of the average of previous wake epochs with eyemovements; OR <20% of the average of wakes epochs without eye movements.EEGPwr VH EEGPwr very high when it is: > the average of previous wakeepochs with eye movements; OR >3 times the average of previous wakeepochs without eye movements. FSP Frontal spindle: 10.5~14 Hz FSPHiCurrent FSPPwr level is high if it is not FSPLwst, not FSPLow and notFSPHst. FSPHst Current FSPPwr level is low if it is not FSPLwst and notFSPLow, AND: > its average over previous SD epochs, OR >80% of itsaverage over previous S2 epochs, OR >3 times its average over previousS1 epochs, OR >4 times its average over previous wake epochs. FSPLowCurrent FSPPwr level is low if it is not FSPLwst, AND: < its averageover previous S1 epochs, OR <1.2 times its average over previous REMepochs, OR <50% of its average over previous S2 epochs. FSPLwst CurrentFSPPwr level is lowest if it is: < its average over previous REM, wakeepochs, or 80% of S1 epochs; OR <30% of its average over previous S2epochs. FSPPwr Value of EEG power spectra of frontal spindle (rangingfrom 10.5~14 Hz) FstWv EEG power spectra of fast waves (ranging from 8to 30 Hz). FstWv Pwr FstWv Pwr is high when it is: High > its averageover previous S1 epochs, AND >7.5 × 10⁶ μV². FstWv Pwr FstWv is low whenit is < its Low average value of previous S1 epochs. FstWv Pwr FstWv isvery high when it is > its VH average value of previous Wake epochs.FEMs Number of Fast Eye Movements: REMs + eye blinks; HBSI The number ofsegments (out of total 10 for each epoch) for which BSI is BSIHi. Each30 second epoch is divided evenly into ten 3 second segments. The EEGpower spectra of each is analyzed independently and categorized. IncrsIncreased compared to last epoch (e.g. Alpha Incrs >0.2 = alphaincreased more than 20% than last epoch) LDE Last determined epoch: theepoch for which a sleep stage was determined and which is immediatelyBEFORE current previous undecided epoch. LFSP The number of segments(out of total 10 for each epoch) for which FSP is FSPLow MA Duration ofdetected movement arousal (in seconds) MslTLow Muscle tone level is Low,if it is: < its average over previous S1, S2 and SD epochs; OR <1.2times its average over previous REM epochs. MslTVH Muscle tone level isvery high, if it is: >2 times its average value of previous S1, S2, SDand REM epochs. MT Movement Time sleep stage NDE Next determined epoch:the epoch for which a sleep stage was determined and which isimmediately AFTER current previous undecided epoch. Noisy The signalsare noisy: more than 50% of the epoch in which signal amplitude ishigher than 200 μV for EEG, 500 μV for EMG and 300 μV for EOGs. PUEPrevious undecided epochs REM Sleep stage REM REMBgrd REM backgroundactivities when: MslTLow, AND AftR, AND REMs >0, AND !BSILwst, AND!AlpPk, AND !FstWv Pwr VH, AND FSPLow REMs Number of detected rapid eyemovement(s) R_M REM or MT R_S1 REM or S1 R_S2 REM or S2 R_W REM or WakeS1 Sleep stage 1 S2 Sleep stage 2 SD Delta (deep) sleep stage (S3 or S4)S2Wvs Spindle, K-Complex found in the epoch Spindle not Frontal spindleactivities are not high high when: the duration of detected spindles<10% of the epoch length AND FSPLow SpnPk Peak found in the FSP sub bandon EEG power spectra Tht EEG theta sub band: 3~7 Hz Tht Pwr Low Thetasub band power of EEG spectra is low when it is: <2.0 times its lowestvalue. W Sleep stage Wake Wakening Wakening activities: when MslTVH,BSIHi or BSIHst, and AlpPwr increased more than 200%. && Logic AND ||Logic OR ! Logic NOT

1. A method of sleep stage determination, comprising: receivingelectrical potentials corresponding to biological signals from anelectrode assembly positioned over a head of a patient; processing thebiological signals to determine EEG signals, EOG signals and EMGsignals; calculating, with a processor, a pre-score based on the EEGsignals, the EOG signals and the EMG signals and a plurality of rules;using said processor for determining based on said plurality of rulesand said pre-score whether the sleep stage can be categorized by thepre-score; checking whether a sleep stage has been categorized based onsaid pre-score using said processor; and when said checking stepdetermines that the sleep stage could not be categorized based on saidpre-score, determining the sleep stage based on at least one epoch. 2.The method of claim 1, wherein the rules are based on empiricallyderived correlations of EEG, EOG and EMG signal activity with one ormore stages of sleep.
 3. The method of claim 1, wherein the electrodeassembly comprises first, second and third electrodes positioned atlocations on or adjacent the forehead area, the first electrode beingpositioned adjacent a nasion area of the head and the second and thirdelectrodes being positioned over respective laterally opposed foreheadareas.
 4. The method of claim 3, wherein the second and third electrodesare positioned above and laterally beyond respective Fp1 and Fp2positions.
 5. The method of claim 1, further comprising, prior to thestep of receiving, positioning a sensing unit comprising the frontalelectrode assembly over the forehead area, the sensing unit beingconfigured to sense electrical potentials corresponding to thebiological signals.
 6. The method of claim 1, wherein in saiddetermining the sleep stage based on at least one epoch step, the sleepstage is determined on an epoch by epoch basis.
 7. The method of claim6, wherein for an epoch, the step of determining includes evaluating theEEG signals, the EOG signals and the EMG signals received during theepoch according to the plurality of rules and assigning a sleep stagecategorization to the epoch.
 8. The method of claim 7, wherein the stepof determining includes evaluating the EEG signals, the EOG signals andthe EMG signals received during a plurality of epochs according to theplurality of rules and assigning a sleep stage categorization to theepoch.
 9. The method of claim 7, wherein the step of determining isbased on previous undecided epochs and last determined epochs and theplurality of rules.
 10. The method of claim 1, further comprisingreceiving further electrical potentials corresponding to body movementof the patient, wherein the determining is also based on the furtherelectrical potentials.
 11. The method of claim 10, further comprisingpositioning one or more body movement sensors in relation to a body ofthe patient away from the head to provide the further electricalpotentials.
 12. The method of claim 11, wherein the one or more sensorscomprise one or more accelerometers.
 13. The method of claim 11, whereinthe one or more sensors comprise one or more electromyographic sensors.